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This study proposes a framework that demonstrates how the perceived value of augmented reality (AR) shopping influences the formation of psychological ownership of product and technology. The mediating role of flow experience and the moderating role of perceived control are identified.

An online survey study recruiting 480 participants who experienced AR shopping was conducted to test the hypotheses.

Functional value is negatively related to psychological ownership of product and technology whereas emotional value shows opposite effects. Flow experience mediates the relationships between functional/emotional value and psychological ownership of product and technology. Perceived control moderates the relationship between emotional value and flow experience, as well as the relationship between functional/emotional value and psychological ownership of product and technology.

The findings suggest the importance of AR’s functional and emotional values in developing psychological ownership of product and technology. To mitigate the negative effect of functional value, AR designers should focus on creating emotionally engaging apps that induce a flow experience, thereby enhancing psychological ownership. Furthermore, AR apps should be designed to empower users with a sense of control in the AR experience.

This research contributes to the AR and psychological ownership literature. It introduces a model that can explain both the formation of psychological ownership of product and psychological ownership of technology, thereby expanding the current understanding. By adding perceived values as antecedents of psychological ownership, it enriches the psychological ownership literature. Moreover, it enhances the flow experience literature by demonstrating the role of flow experience in the formation of psychological ownership of product and technology.

This study aims to explore the spatial impact of an increase in the minimum wage on the labor productivity of star-rated hotels in China.

The impact is analyzed by using the dynamic spatial Durbin model.

The authors find a U-shaped link between the increase in minimum wage and labor productivity of star-rated hotels. The long-term impact of a minimum wage increase has a greater influence on labor productivity than its short-term effects. While there is no notable spatial spillover impact observed in the sample of 31 provinces in China, the authors do identify a spatial spillover effect of the minimum wage rises on the labor productivity of star-rated hotels in the central area. Furthermore, they observe heterogeneity across China. The eastern and western regions exhibit a U-shaped relationship, whereas the central region exhibits an inverted U-shaped relationship.

The findings of this study allow government agencies to get a more comprehensive comprehension of the actual consequences of minimum wage hikes on the tourism and hospitality sector, thereby establishing a solid basis for them to develop appropriate policies. Moreover, it offers a variety of suggestions aimed at enhancing the quality and efficiency of hotel management.

Research on the effects of minimum wage standards is scant in the hospitality industry. Based on human capital investment theory, this study examines the effect of the minimum wage standard hikes on labor productivity of star-rated hotels from the spatial perspective, filling the existing research gap.

The purpose of this study is to investigate the impact of political skills of faculty members in Chinese universities on their tendency to obtain knowledge shared by their colleagues, as well as their tendency to share knowledge with their colleagues. Moreover, this study investigated the role of collectivistic culture in a workplace as the moderating variable that may influence the effect of political skill on knowledge sharing.

Survey data were obtained from 387 faculty members across six universities located in the northern and the central cities of China. Partial least squares structural equation modeling was used as the statistical method for data analysis.

The results provided significant evidence that supported the positive effect of political skill on knowledge sharing. Furthermore, the moderating effect analysis showed that in the workplaces that had strong collectivist culture, the degree to which employees obtained knowledge shared by others, as well as the willingness of employees to share their knowledge to others, was more likely to happen as compared to that in the workplaces that had a weak collectivist culture.

As part of human capital development policies, political skill training could be an intervention to promote knowledge sharing among faculty members. The training may be particularly helpful to promote knowledge sharing in a workplace that adopts individualistic culture more than in a workplace that adopts collectivistic culture.

This study provided new evidence that extended previous studies by unveiling the moderating effect of collectivist culture in a workplace that was found to reduce the effect of political skill on knowledge sharing.

In the past 10 years, the scale of running events in China has increased dramatically, and the forms of running events have also become rich and diverse. Running is not only a social phenomenon but also a historical and cultural phenomenon as an organic part of human culture with its own sociological values in China. This chapter offers insight into the development of Chinese running culture and how this has emerged from ancient and modern Chinese running cultures based on Foucault's disciplinary power theory, biopower and the technologies of the self. This chapter argues that running culture in China constructs the subjectivity of the Chinese runners under the joint action of the technologies of power and the technologies of the self. The findings acknowledge how Chinese Runners present and express themselves by showing a ‘sense of presence’. Runners illustrate the implicit or explicit meaning and value of a particular way of life through running. Runners regard running as the technology of the self for self-expression and self-creation so that individuals can control their bodies and soul, thoughts, behaviours and ways of existence. Emerging technologies of power provide possibilities for the production of running culture in China, and the current policy under the technologies of power meets the needs of runners. In Chinese running culture, power was not oppressive but productive.

The accurate prediction of driving torque demand is essential for the development of motion controllers for mobile robots on complex terrains. This paper aims to propose a hybrid model of torque prediction, adaptive EC-GPR, for mobile robots to address the problem of estimating the required driving torque with unknown terrain disturbances.

An error compensation (EC) framework is used, and the preliminary prediction driving torque value is achieved using Gaussian process regression (GPR). The error is predicted using a continuous hidden Markov model to generate compensation for the prediction residual caused by terrain disturbances and uncertainties. As the final step, a gain coefficient is used to adaptively tune the significance of the compensation term through parameter resetting. The proposed model is verified on a sample set, including the driving torque of a mobile robot on three different sandy terrains with two driving modes.

The results show that the adaptive EC-GPR yields the highest prediction accuracy when compared with existing methods.

It is demonstrated that the proposed model can predict the driving torque accurately for mobile robots in an unconstructed environment without terrain identification.

This study aims to identify which types of information quality influence purchase intentions the most in live streaming commerce and to examine the role of network size in this context.

We propose a model to investigate the correlation among the quality of different information in live streaming commerce, consumer trust, network size and purchase intention. An empirical analysis of 505 questionnaires was conducted by constructing a structural equation model.

The empirical findings indicate that information quality can directly enhance purchase intention and exert an indirect influence through the mediating factors of trust in products and streamers. Perceived network size positively moderates the relationship between information quality and trust in products. Of the five types of information, the quality of bullet-screen comments information is most important to consumers.

This study represents the first systematic analysis of how the quality of multiple types of information in live streaming commerce influences consumer trust and purchase intention, integrated within a unified framework. It uniquely introduces network size as a moderating variable, offering both theoretical insights and practical guidance for balancing information quality with network size in live streaming commerce environments.

Autonomous underwater vehicle (AUV) is widely used in resource prospection and underwater detection due to its excellent performance. This study considers input saturation, nonlinear model uncertainties and external ocean current disturbances. The containment errors can be limited to a small neighborhood of zero in finite time by employing control strategy. The control strategy can keep errors within a certain range between the trajectory followed by AUVs and their intended targets. This can mitigate the issues of collisions and disruptions in communication which may arise from AUVs being in close proximity or excessively distant from each other.

The tracking errors are constrained. Based on the directed communication topology, a cooperative formation control algorithm for multi-AUV systems with constrained errors is designed. By using the saturation function, state observers are designed to estimate the AUV’s velocity in six degrees of freedom. A new virtual control algorithm is designed through combining backstepping technique and the tan-type barrier Lyapunov function. Neural networks are used to estimate and compensate for the nonlinear model uncertainties and external ocean current disturbances. A neural network adaptive law is designed.

The containment errors can be limited to a small neighborhood of zero in finite time so that follower AUVs can arrive at the convex hull consisting of leader AUVs within finite time. The validity of the results is indicated by simulations.

The state observers are designed to approximate the speed of the AUV and improve the accuracy of the control method. The anti-saturation function and neural network adaptive law are designed to deal with input saturation and general disturbances, respectively. It can ensure the safety and reliability of the multiple AUV systems.

Firms are increasingly digitalizing their business processes and expanding them into digital platforms, which are believed to generate digital and relational resources that can facilitate and deliver innovations for firms. Instead of focusing on the extent of digital integration capability (DI), this paper seeks to empirically evaluate whether the DI asymmetry between the buyer and supplier firms influences bilateral information sharing and the buyer’s product innovation. We also examine the moderating effects of firms’ external (environmental dynamism) and internal (innovative climate) environments on these relationships.

Primary and secondary archival data on 180 buyer-supplier Chinese dyadic relationships were collected and analyzed using multiple linear regression models. Additionally, the Process macro was used to shed a nuanced light on the moderation effects of environmental dynamism and innovative climate.

The results show that DI asymmetry negatively impacts buyer firms’ product innovation through decreased information sharing. Environmental dynamism weakens the negative relationship between DI asymmetry and information sharing. Meanwhile, the innovative climate negatively moderates the relationship between information sharing and product innovation.

This study adds knowledge to the literature regarding the dark side of “one-sided digitalization.” By exploring the influences of unbalanced DI in buyer-supplier relationships, this study yields essential theoretical and managerial implications for product innovation success in a digital era.

This study aims to integrate the componential model of creativity and innovation with a participative safety perspective to investigate the association between autonomy support and innovation as well as the organizational factors that strengthen this association. Specifically, the study suggests that autonomy support is more effective in fostering innovation in organizations characterized by higher levels of trust, strong organizational fairness and effective communication.

The proposed hypotheses were investigated using moderated mediation models with panel data collected over four waves.

This study found that autonomy support positively contributes to organizational innovation. Moderation analyses demonstrated that trust, perceptions of fairness and communication strengthen the effect of autonomy support on innovation.

This study is the first to demonstrate the moderating roles of various organizational contexts (i.e. trust, fairness perception and communication) in the association between autonomy support and innovation and to investigate the role of trust as a mediating moderator.

The purpose of this study is to formulate a new class of vehicle routing problem with an objective to minimise the total cost of raw material collection and derive a new approach to solve optimization problems. This study can help to select the optimum number of suppliers based on cost.

To model the raw material vehicle routing problem, a mixed integer linear programming (MILP) problem is formulated. An interesting phenomenon added to the proposed problem is that there is no compulsion to visit all suppliers. To guarantee the demand of semiconductor industry, all visited suppliers should reach a given raw material capacity requirement. To solve the proposed model, the authors developed a novel hybrid approach that is a combination of block and edge recombination approaches. To avoid bias, the authors compare the results of the proposed methodology with other known approaches, such as genetic algorithms (GAs) and ant colony optimisation (ACO).

The findings indicate that the proposed model can be useful in industries, where multiple suppliers are used. The proposed hybrid approach provides a better sequence of suppliers compared to other heuristic techniques.

The data used in the proposed model is generated based on previous literature. The problem derives from the assumption that semiconductor industries use a variety of raw materials.

This study provides a new model and approach that can help practitioners and policymakers select suppliers based on their logistics costs.

This study provides two important contributions in the context of the supply chain. First, it provides a new variant of the vehicle routing problem in consideration of raw material collection; and second, it provides a new approach to solving optimisation problems.